Single- and Multi-Objective Optimization Frameworks of Shape Design of Tubular Linear Synchronous Motor

Araby Mahdy, Abdullah Shaheen, Ragab El-Sehiemy (), Ahmed Ginidi and Saad F. Al-Gahtani
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Araby Mahdy: Department of Mechanical Engineering, Faculty of Engineering, Suez University, Suez 43533, Egypt
Abdullah Shaheen: Department of Electrical Engineering, Faculty of Engineering, Suez University, Suez 43533, Egypt
Ragab El-Sehiemy: Department of Electrical Engineering, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh 33516, Egypt
Ahmed Ginidi: Department of Electrical Engineering, Faculty of Engineering, Suez University, Suez 43533, Egypt
Saad F. Al-Gahtani: Department of Electrical Power Engineering, Faculty of Engineering, King Khalid University, Abha 61421, Saudi Arabia

Energies, 2023, vol. 16, issue 5, 1-27

Abstract: The shape design of the Tubular Linear Synchronous Motor (TLSM) is a critical engineeri ng optimization problem which was handled as single- and multi-objective optimization frameworks. However, the different practical constraints for the TLSM design must be efficiently guaranteed. This paper proposes a developed multi-objective shape design of the TLSM to maximize the operating force and minimize the flux saturation. In this regard, a Multi-objective Grey Wolf Optimizer (MGWO) is developed, including an outside archive with a predetermined size that is integrated for storing and retrieving Pareto optimal solutions. Using this knowledge, the grey wolf social structure would then be established, and, in the multi-objective searching environments, grey wolf hunting behavior would then be replicated. The superiority and effectiveness of the developed MGWO is assessed in comparison to the Multi-objective Flower Pollination Algorithm (MFPA), Multi-objective Lichtenberg Algorithm (MOLA), and Multi-objective Grasshopper Optimization Algorithm (MGOA). The outcomes illustrate that the developed MGWO provides an average improvement of 73.46%, 19.07%, and 15.15% compared to MFPA, MOLA, and MGOA, respectively. The validation of the developed MGWO is extended for a multi-objective form of welded beam design (WBD) by simultaneously minimizing the deflection and the manufacturing costs. Similar findings are obtained with different reference points, the developed MGWO provides an average improvement of 2.8%, 0.7%, and 3.04% compared to MFPA, MOLA, and MGOA, respectively.

Keywords: grey wolf algorithm; pareto archive; multi-objective shape design of tubular linear synchronous motor; maximizing the operating force; minimizing the flux saturation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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